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» On the Expressive Power of QLTL
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106
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CSB
2005
IEEE
137views Bioinformatics» more  CSB 2005»
15 years 6 months ago
A Learned Comparative Expression Measure for Affymetrix GeneChip DNA Microarrays
Perhaps the most common question that a microarray study can ask is, “Between two given biological conditions, which genes exhibit changed expression levels?” Existing methods...
Will Sheffler, Eli Upfal, John Sedivy, William Sta...
BMCBI
2010
124views more  BMCBI 2010»
15 years 25 days ago
A factor model to analyze heterogeneity in gene expression
Background: Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene d...
Yuna Blum, Guillaume Le Mignon, Sandrine Lagarrigu...
124
Voted
BMCBI
2006
170views more  BMCBI 2006»
15 years 23 days ago
Biclustering of gene expression data by non-smooth non-negative matrix factorization
Background: The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of gene...
Pedro Carmona-Saez, Roberto D. Pascual-Marqui, Fra...
BMCBI
2006
109views more  BMCBI 2006»
15 years 23 days ago
Integrated analysis of gene expression by association rules discovery
Background: Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditi...
Pedro Carmona-Saez, Monica Chagoyen, Andrés...
BMCBI
2007
176views more  BMCBI 2007»
15 years 25 days ago
Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue
Background: Micro- and macroarray technologies help acquire thousands of gene expression patterns covering important biological processes during plant ontogeny. Particularly, fait...
Marc Strickert, Nese Sreenivasulu, Björn Usad...